Jacobian Determinant/ mult. variable implicit differentiation

In summary, the problem involves finding the derivative of z with respect to x, using the Jacobian determinant. The Jacobian determinant is a helpful tool for evaluating partial derivatives when there are multiple equations and variables. The solution involves setting up two Jacobians and using the chain rule to cancel out some terms, ultimately leading to the desired derivative.
  • #1
Isaac Wiebe
6
0

Homework Statement


Let F: x^2 + y^2 - z^2 + 2xy - 1 = 0 and G: x^3 + y^3 - 5y - 4 = 0. Calculate dz/dx. Note: This is NOT the partial derivative ∂z/∂x.

I do not need help in taking the derivative of many polynomials. What I need help in is setting up a Jacobian determinant to evaluate this.


Homework Equations



The Jacobian determinant, bit tough to explain in a short period of space. Exceptionally helpful with many equations with as many variables as equations, in which the partial derivative can be evaluated by the Jacobian Determinant.



The Attempt at a Solution


Okay, so dz/dx = [∂(F, G) /∂(z, y)] / ∂(F, G) / ∂(x, y) * (-1), but this is incorrect as this is ∂z/∂y. Essentially I need to know, what is a function of what, and how can I evaluate this? I do not care necessarily for the answer, simply for the setup.
 
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  • #2
The ultimate independent variable is x. G relates x and y so y is only function of x:y=y(x).
F is a relation among x, y, z. z depends both on y and x: z=z(x,y(x)). ehild
 
  • #3
Here is the motivation
F(x,y,z)=0
G(x,y,z)=0
0=dF=Fx dx+Fy dy+Fz dz
0=dG=Gx dx+Gy dy+Gz dz
first we find
0=(Gy dF - Fy dG)/dx
which will have the Jacobians you seek
then think it through in general

What happens is you get F,G,x,y in one Jacobian and F,G,y,z in the other and F,G,y effectively cancel (chain rule) leaving dz/dx
 
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Related to Jacobian Determinant/ mult. variable implicit differentiation

1. What is the Jacobian Determinant in multivariable calculus?

The Jacobian Determinant is a concept in multivariable calculus that is used to measure how a small change in multiple variables affects the output of a function. It is represented by a matrix of partial derivatives and is used in various applications such as implicit differentiation and change of variables in multiple integrals.

2. How is the Jacobian Determinant calculated?

The Jacobian Determinant is calculated by taking the partial derivatives of a function with respect to each of its variables and arranging them in a matrix. Then, the determinant of this matrix is calculated to obtain the value of the Jacobian Determinant. It can also be calculated using the chain rule for multiple variables.

3. What is the significance of the Jacobian Determinant in multivariable implicit differentiation?

The Jacobian Determinant is used in multivariable implicit differentiation to find the derivative of a function with respect to a variable that is not explicitly defined in the function. It helps to determine how the output of the function changes when the input variables are changed, even if the function cannot be solved explicitly for the desired variable.

4. Can the Jacobian Determinant be negative?

Yes, the Jacobian Determinant can be negative. The sign of the Jacobian Determinant depends on the orientation of the coordinate system. If the orientation is changed, the sign of the Jacobian Determinant will also change. However, the absolute value of the Jacobian Determinant remains the same.

5. What are some real-life applications of the Jacobian Determinant?

The Jacobian Determinant has various real-life applications, such as in physics, economics, and engineering. It is used to calculate the change in a system's variables, such as velocity and position, over time. It is also used in optimization problems, where it helps to determine the direction of maximum change in a function. Additionally, it is used in image processing and computer graphics to transform and manipulate images.

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